Spring Ai Playground

Spring AI Playground

**Safe Local Execution Layer for AI Agent Tools**

Spring AI Playground is a cross-platform desktop app for building, testing, validating, and executing MCP tools in a controlled local environment. It helps you create reusable MCP tools once and use them across macOS, Windows, and Linux through a self-contained runtime. Unlike platforms that focus primarily on generating agents or authoring tools, Spring AI Playground focuses on making the tools it manages inside the app safer and easier to inspect before reuse.

**No pass, no run.**

Every tool you build earns a **Local Pass** — a local test-run with your sample arguments. Only passing tools are added live to the built-in MCP server and become callable from Agentic Chat. A tool that has not passed is never exposed to an agent.

**Security scope.** The in-process sandbox is defense-in-depth for the local build-and-vet loop. It is not adversarial-grade isolation and not a gateway. To run tool code you do not trust, nest it in container or microVM isolation. See [Isolation tiers](https://spring-ai-community.github.io/spring-ai-playground/safety-architecture/#isolation-tiers).

Safe execution does not end at publication. Every chat, tool call, vector lookup, and MCP invocation that runs in the app lands in the built-in **Observability dashboards** spanning Overview, Tokens & Cost, AI Models, Tool Studio, MCP Servers, MCP Inspector, Vector Database, Agentic Chat, Safety, Host, Ollama, Web Application, Logs, and Traces, backed by a ring buffer with dated disk persistence. Drill from a row into the trace timeline and raw spans, jump to the conversation thread, and deep-link back into Agentic Chat — so the tools you let an agent call are also the tools you can see in detail after the fact.

In Tool Studio, new or updated built-in tools are test-run before they are published to the built-in MCP server. You do not need to know Java, Spring, or JVM internals to use it. If you can install a desktop